Role Title Analyst II Data Science - Pricing Deployments Location Colombia About the Role Are you passionate about pricing in the Insurance Industry? Would you like to join a dedicated team responsible for deploying pricing programs across all our retail lines in United States? This is then your next job! The USDS Earnix Design Excellence and Support team is looking for a Data Science Analyst I or II to design and build major pricing programs in Earnix and develop best-in‑class practices for pricing deployment design. The Earnix initiative is transforming our pricing ecosystem and post‑modeling processes to increase speed to market and deploy more sophisticated models across all lines of business. This role will develop deep expertise in deploying, maintaining, and monitoring Liberty Mutual's pricing models, collaborating heavily with data science, product delivery, and tech teams. It will also play a key role in establishing new Earnix capabilities to scale the speed and efficiency of implementing pricing programs and other use cases. Key Responsibilities Design best‑in‑class capabilities to support post‑modeling activities, including calibration, dislocation, and filing. Build USDS pricing programs in Earnix. Design and implement other use cases of Earnix as a rating engine. Ensure accuracy of all pricing and non‑pricing outputs from Earnix. Design and maintain rigorous data models for Earnix analytical projects and API. As required, troubleshoot and support post launch queries and issues. Improve and automate processes where applicable. Engage with the data science community and participates in cross‑functional working groups. This role may be for you if you Love insurance rating programs and want to get a deeper understanding of how they work. Frequently bring voices together to find patterns in business problems. Are comfortable challenging the status quo to make systems simpler, more robust, and scalable. Enjoy documenting and sharing best practices to accelerate the whole team. Get excited by delivering business critical, production‑ready products. Qualifications Must have English C1 Competencies typically acquired through a Master’s degree (scientific field of study) and 2 to 3 years of relevant experience. Solid knowledge of predictive analytics techniques and statistical diagnostics of models. Foundational/intermediate knowledge of predictive toolset. Foundational general programming Python skills preferred. Strong understanding of rating algorithm structures, including their components, inputs, and outputs, is highly preferred. Knowledge of Earnix or similar rating tools is a plus. Demonstrated ability to exchange ideas and convey complex information clearly and concisely. Has a value-driven perspective about understanding of work context and impact. Demonstrate business professional proficiency in English with excellent written and verbal communication skills, as all work and communication are conducted in English. #J-18808-Ljbffr